Abstract
ARMOR aspires to use all available information from diverse sources to enhance the management of epilepsy in terms of diagnosis, home monitoring and evaluating the efficacy of treatment. In this chapter we introduce a novel approach aimed at achieving this goal through smart use of available data. The primary focus of the approach is to use magnetoencephalography (MEG) or high-density electroencephalography (hdEEG), when they are available, to improve the effectiveness of routine electroencephalography (EEG) tests. In a nutshell, we acknowledge that with the currently available hardware it is not possible to record MEG or hdEEG on a routine basis, so we want to use one or few such measurements to develop a personalized neurophysiological model of the epileptic condition and then use the model to derive specific biomarkers, which can be measured with simple and more easily available techniques such as few-channel EEG, electrocardiogram (ECG), electrodermal response (EDR) etc. Thus the goal is to use MEG or hdEEG for background reference and a base for development of biomarkers that can address specific clinical questions for a specific patient using simpler devices, which can be easily used in the home environment, such as few EEG electrodes. Although as stated above the primary focus of the approach is the smart use of advanced neurophysiological techniques, such as MEG or hdEEG, the methods developed here can be used with simpler data, such as low-density EEG (e.g. 21-electrode 10–20 system), which is largely available for most epilepsy patients, to significantly improve the EEG setup for further routine measurements.
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Notes
- 1.
These data were recorded as part of a routine clinical examination at the MINDLab Core Experimental Facility at the Center of Functionally Integrative Neuroscience (CFIN), Aarhus University and Aarhus University Hospitals, Aarhus, Denmark.
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Poghosyan, V., Ioannides, A.A. (2015). Personalized Management of Epilepsy Through Smart Use of EEG and Detailed MEG Analysis. In: Voros, N., Antonopoulos, C. (eds) Cyberphysical Systems for Epilepsy and Related Brain Disorders. Springer, Cham. https://doi.org/10.1007/978-3-319-20049-1_13
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DOI: https://doi.org/10.1007/978-3-319-20049-1_13
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